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首页> 外文期刊>Global change biology >From remotely‐sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II—Harnessing data
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From remotely‐sensed solar‐induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II—Harnessing data

机译:从遥感太阳能诱导的叶绿素荧光到生态系统结构、功能和服务:第二部分——利用数据

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Abstract Although our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in‐situ SIF observing capability especially in “data desert” regions, improving cross‐instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.
机译:摘要 尽管我国对太阳诱导叶绿素荧光(SIF)的观测能力快速增长,但SIF数据集的质量和一致性仍处于积极的研发阶段。因此,不同尺度的SIF数据集之间存在相当大的不一致,并且它们的广泛应用导致了相互矛盾的结果。本综述是两篇配套综述中的第二篇,以数据为导向。它旨在 (1) 综合现有 SIF 数据集的多样性、规模和不确定性,(2) 综合生态学、农业、水文学、气候和社会经济学领域的各种应用,以及 (3) 阐明此类数据不一致如何与(Sun 等人,2023 年)中列出的理论复杂性叠加可能影响各种应用的过程解释并导致不一致的结果。我们强调,准确解释SIF与其他生态指标之间的功能关系取决于对SIF数据质量和不确定性的完全理解。SIF观测中的偏差和不确定性会严重混淆对其关系的解释,以及这种关系如何对环境变化做出反应。基于我们的综合,我们总结了当前SIF观测中存在的差距和不确定性。此外,我们还提出了我们的观点,以帮助改善气候变化下的生态系统结构、功能和服务所需的创新,包括提高原位SIF观测能力,特别是在“数据沙漠”地区,提高跨仪器数据标准化和网络协调,以及通过充分利用理论和数据推进应用。

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